Forward Deployed Solution Engineer (Applied AI FDE)

Join ServiceNow's Applied AI Forward Deployed Engineering (FDE) team as a Senior Forward Deployed Software Engineer (FDSE). In this role, you will partner with strategic customers to build intelligent, scalable AI solutions that address their most critical challenges. You will own the entire software stack, from backend services to LLM pipelines and front-end integrations, and deliver production-ready solutions in agile sprints. Your work will have a significant impact on the Now AI Platform and the broader enterprise.

- You are a systems-minded, AI-native engineer who ships real software. You own the full stack—and are equally motivated by elegant APIs, intuitive UIs, and scalable orchestration pipelines. You think like a product-minded CTO, balancing creativity with pragmatism to deliver impact
- Performance & observability: Skilled in debugging distributed systems, tuning for latency, and implementing monitoring
- Field readiness: Able to travel up to 30% to embed onsite and deliver where it matters
- Product sensibility: Prioritize for user value, MVP iteration, and long-term scale
- You embed deeply with customer teams, diagnose root problems, and architect AI-powered workflows that run at scale. You don’t just debug code—you debug systems, context, and customer pain points
- Relevant Experience: 10+ years of software engineering, including 2+ years building systems in customer-facing or embedded roles
- DevOps fluency: Experience deploying in AWS, Azure, or GCP with CI/CD, containers, and infra-as-code
- LLM tooling: Familiarity with LangChain, Semantic Kernel, prompt chaining, vector search, and context management
- Platform mindset: Can contribute to shared SDKs and tools, raising engineering velocity for the whole org
- Engineering depth: Strength in backend (Python, Node.js, Java), frontend (React, Angular), APIs (REST/GraphQL)
- Experience: In leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI’s potential impact on the function or industry
- System architecture: Proven ability to design and implement AI-native software in production environments
- Contributions to dev experience tooling, frameworks, or reusable AI scaffolds
- Track record of production deployments in secure, regulated enterprise environments
- Experience integrating AI into SaaS platforms like ServiceNow or Salesforce